Stan Tsing

828 citations
10 papers · 661 · h-index 10

Impact in

    • Inflammatory mediators and NSAID effects
    • Pharmacogenetics and Drug Metabolism
  • Biochemistry top 10%
    • Eicosanoids and Hypertension Pharmacology

Papers in

    • Viral Infectious Diseases and Gene Expression in Insects 3
    • Glycosylation and Glycoproteins Research 2
    • Melanoma and MAPK Pathways 2
    • Chronic Lymphocytic Leukemia Research 2

Stan Tsing

10 papers receiving 629 citations

Peers

Stan Tsing
Comparison fields: 5 of 88
  • Pharmacology 213
  • Biochemistry 76
  • Pharmacology 53
  • Genetics 56
  • Immunology 99
Replace D.H. Ives with:
D.H. Ives United States
Sarah A. Head United States
Jonny Wijkander Sweden
R. R. Martel United States
Ching-Shih Chen United States
Delano V. Young United States
Beth A. Strifler United States
Zsolt Lőrincz Hungary
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Stan Tsing relative to D.H. Ives United States D.H. Ives's profile →
Citations per field
00.5×10×16×
D.H. Ives · 1×
Citations per year

Countries citing papers authored by Stan Tsing

Since Specialization
Citations

This map shows the geographic impact of Stan Tsing's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Stan Tsing with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stan Tsing more than expected).

Fields of papers citing papers by Stan Tsing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stan Tsing. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Stan Tsing. The network helps show where Stan Tsing may publish in the future.

Co-authors

The 25 scholars most cited alongside Stan Tsing, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Stan Tsing Line = papers co-authored together Stan Tsing links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1 1994314
2 200763
3 200852
4 199652
5 201042
6 200741
7 201034
8 198624
9 199423
10 199516

About Stan Tsing

Stan Tsing is a scholar working on Molecular Biology, Genetics, Animal Science and Zoology, Computational Theory and Mathematics and Immunology, having authored 10 papers that have together received 661 indexed citations. Recurring topics across this work include Viral Infectious Diseases and Gene Expression in Insects (3 papers), Glycosylation and Glycoproteins Research (2 papers), Melanoma and MAPK Pathways (2 papers), Chronic Lymphocytic Leukemia Research (2 papers), Computational Drug Discovery Methods (2 papers), Cancer Mechanisms and Therapy (1 paper), NF-κB Signaling Pathways (1 paper) and Meat and Animal Product Quality (1 paper). The work is most often cited by research in Pharmacology (213 citations), Biochemistry (76 citations), Pharmacology (53 citations), Genetics (56 citations) and Immunology (99 citations). Stan Tsing has collaborated with scholars based in United States, Poland and Switzerland. Frequent co-authors include Jim Barnett, Chinh Bach, Hardy Chan, David E. Shaw, D.H. Ives, José Ednésio da Cruz Freire, Rebecca Mackenzie, C S Ramesha, Elliott Sigal and Joan M. Chow. Their work appears in journals such as Protein Expression and Purification, The Journal of Immunology, Bioorganic & Medicinal Chemistry Letters, Biochemical Journal and Journal of Molecular Biology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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